The development of technology has changed various sectors in life to be smart, including tourism. This study aims to analyze the effect of smart tourism technology attributes on visit intention and visiting tourist destinations. This study used a sample of 324 tourists in West Java Province, Indonesia. Partial Least Square is applied to test the relationship between variables. The results of the study revealed that smart tourism technology attributes such as smart information systems, smart tourism management, smart sightseeing, e-commerce systems, smart safety, smart traffic, and virtual tourism objects affect visit intention. The study also revealed the effect of visiting intentions on visits to tourist destinations. The findings of this study provide the basis for formulating strategies for implementing smart tourism technology that is appropriate in attracting tourist visits.
Tourism contributes to regional development and generates income for destinations. However, in many cases, the growth of tourist numbers does not necessarily result in an equivalent rise in economic contribution. The search for quality tourists over the quantity of tourists is certainly an important goal of regional development managers, but the efforts required to implement such an approach, especially the detailed documentation of tourist behavior while visiting the region, pose a challenge for most. This is perhaps why the analysis of quality vs quantity of tourists has been limited. This study focuses on the Great Ocean Road Region in Australia; an area that is experiencing increased visitor numbers but is not seeing commensurate economic growth. A fine-grained analysis of the international and domestic tourists is employed to determine behavior-based tourist quality, including the measurement of their traveling behavior, overnight visitation pattern, expenditure, and regional dispersal. Data was collected from 311 domestic tourists and 562 international tourists. Descriptive statistical methods were used in analyzing data. Results indicate that the domestic tourists were of a higher quality than the international tourists; they stayed longer, spent more, and were more widespread across the region than the international tourists. Hence, high-quality tourists can be a valuable resource and should be a priority for regional tourism development.
This paper aims to investigate the tourist behaviour towards smart tourism in the case of emerging smart destinations. The extended model of theory of planned behaviour (TPB) is proposed as a tool to predict the relationship between applying smart tourism technology and tourist behaviour in selecting and visiting the destination. Using the city of Bandung, Indonesia as a case study, data was collected using a structured questionnaire from 524 domestic tourists in several emerging smart destinations. The confirmatory factor analysis was utilised to test the construct validity and reliability of the model, while Partial Least Squares (PLS) modelling was employed to assess the hypotheses developed. The results show that the extended TPB model can reasonably predict the tourist behaviour towards smart tourism, suggesting its applicability to emerging smart destinations. Smart tourism technology directly affects tourists’ attitude, subjective norms, and tourists perceived behavioural control, resulting in their travel intention. Also, their planned behaviour mediates the relationship between smart tourism technology and tourist decision in selecting and visiting destinations. Identifying predictors of tourist behaviour towards smart tourism provides a more accurate forecast of tourist demand, thereby enabling policymakers to tailor and implement a more comprehensive smart tourism planning and development
Since the coronavirus pandemic hit Indonesia, tourists have become more careful when doing tourist activities. Natural or outdoor tourist destinations are assumed as safe and preferable destinations because they have the lowest risk of coronavirus transmission. One of the activities that can be done in natural or outdoor tourist destinations is camping. Using the AIDA (Attention, Interest, Desire, and Action) Model, this research was conducted to determine how much tourists are interested in camping, especially in South Bandung, West Java, Indonesia, as it has many natural tourist destinations with camping areas. This study uses a quantitative descriptive method, frequency analysis techniques, and scoring analysis. Samples were taken using a stratified random sampling technique to 111 respondents. Respondents are tourists who know or have visited one of the three natural tourist destinations in South Bandung, used as samples, namely Mount Puntang, Ranca Upas, and Rancabali. The results show that tourists are quite interested in camping as an alternative tourism activity during the coronavirus pandemic. However, they have some limitations or prerequisites in visiting the camping area during these uncertain times.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.